Method for enhancing the visibility of blood vessels in color images and visualization systems implementing the method

ABSTRACT

A method of enhancing the visibility of blood vessels in a colour image captured by an image capturing device of a medical device, including, for at least some of the pixels of the image, the steps of: (a) processing data obtained from a first colour channel together with data obtained from a second colour channel to determine a value of a first parameter indicative of the intensity in the red spectrum relative to the total intensity of said pixel; (b) using said value of said first parameter and a first value of a user parameter to alter said pixel, the first value of the user parameter being based on user input, and wherein the strength of the alteration is dependent on both the value of said first parameter and the first value of said user parameter.

The present application is a continuation-in-part of InternationalApplication No. PCT/EP2019/073483, filed Sep. 3, 2019, which claimspriority from European Application No. 18193186, filed Sep. 7, 2018;said applications are incorporated herein by reference in theirentirety.

TECHNICAL FIELD

The disclosure relates to visualization systems including videoscopeswith image sensors to capture images of patients. More specifically, thedisclosure relates to a method of enhancing the visibility of bloodvessels in color images captured by the image sensors, a method foridentifying vascular structures, and a visualization system to implementthe method.

BACKGROUND OF THE DISCLOSURE

Medical videoscopes comprise endoscopes, colonoscopes, ear-nose-throatscopes, duodenoscopes, and any other medical device having an imagesensor configured to obtain images of views of a patient. The term“patient” herein includes humans and animals. Portable medical monitorscan be communicativelly coupled to the medical videoscopes to receiveimage data therefrom and present images corresponding to the image dataon a display module of the monitor.

Videoscopes are made for various procedures and may have differenttechnical characteristics suited for the procedure they are designed toperform, based on the age of the device, or for other reasons. Anendoscope is a type of a videoscope. FIG. 1a is a perspective view of avideoscope, e.g. endoscope 1 comprising a handle 2 with an articulationlever 4 and an insertion tube 3 having a proximal end 3 a and a distalend 3 b. An articulation tube 5 having an image sensor 6 is disposed atdistal end 3 b. The image sensor captures optical images and transmitsimage data corresponding to the images via a cable 12 to a connector 13.Connector 13 is insertable into a connector port of a monitor to presentgraphical images corresponding to the optical images with a displaymodule of the monitor. Movement of articulation lever 4 reorients thefield of view of image sensor 6.

Another endoscope, described in commonly owned U.S. Patent ApplicationNo. 2019/0223694, has an insertion tube with an internal working channeland a connector at the handle adapted for the attachment of a syringe. Arecess is adapted to accommodate a cylindrical body of the syringe whenthe syringe is attached to the connector. The endoscope is adapted toperform bronchoalveolar lavage, a procedure for obtaining samples,through the working channel, of organic material from a lung segment ofa patient.

A videoscope can also comprise a endobronchial tube with an imagesensor, as described in commonly owned U.S. Pat. Nos. 10,321,804 and10,406,309. The endobronchial tube comprises a tube having a wall, afirst inflatable cuff, a second lumen having an open distal end, asecond inflatable cuff, a dedicated image sensor lumen in the wall, animage sensor, and an illumination source within the dedicated imagesensor lumen at the distal end thereof. The endobronchial tube mayinclude a dedicated cleaning nozzle arrangement embedded in the wall ofthe tube.

A videoscope can also comprise a endotracheal tube with an image sensor,as described in commonly owned U.S. Pat. No. 10,478,054. Theendotracheal tube comprises a tube having a wall defining a ventilationlumen, an image sensor, and an illumination source within a dedicatedimage sensor lumen at the distal end of the endotracheal tube.

A videoscope can also comprise a video laryngoscope, as described incommonly owned U.S. Pat. No. 9,854,962, known as the King Vision™ aBladeVideo Laryngoscope. The video laryngoscope includes a housing includinga display screen, a battery compartment, and a blade. The blade includesan open channel provided to guide insertion of an endotracheal tube. Animage sensor is positioned at a distal end of the blade. The imagesensor can be part of the blade or can be connected to the housing andintroduced into a cavity of a disposable blade.

Videoscopes can be used to guide insertion of other medical devices,such as endotracheal tubes and tools used to collect tissue or fluidsamples. Physicians may also utilize images obtained with thevideoscopes to analyze tissues and body structures. For example, changesin the vascular structure of internal cavities may be indicative of anumber of diseases, such as autoimmune diseases and cancers. However, itmay be difficult for medical personnel to correctly and preciselyanalyse the vascular structures since the blood vessels may blend inwith the surrounding tissue types.

The visibility of the blood vessels may be improved by providing themedical device with an additional light source emitting light with anarrow wavelength that is selected so that blood vessels have a highabsorption of the light relative to the surrounding tissue. This will,however, increase the cost of the medical device and furthermore changethe colors of the resulting image. The change in the colors may make itmore difficult for medical personnel to navigate the medical device and,furthermore, more difficult to examine changes in other tissue types ofthe internal cavities that may be indicative of a pathologicalcondition.

U.S. Pat. No. 6,956,602 discloses an apparatus that includes a leveladjusting circuit that increases a gain of a G (or B) signal output froma color conversion circuit, a binarization circuit that forms abinarized image from this G signal, and an edge detection circuit thatextracts blood vessel position signals through edge detection based onthis binarized signal. Then, the apparatus extracts RGB color signalsmaking up a blood vessel image by using the above-described blood vesselposition signals, increases the gains of these blood vessel colorsignals and then adds the blood vessel color signals to the colorsignals of an original image. It may, however, be difficult to preciselydetermine the location of the blood vessels in the image. Thus, areas ofthe image originating from blood vessels may not be enhanced whereasareas of the images not originating from blood vessels may be enhanced.

Thus, it remains a problem to provide an improved method/device/systemfor enhancing the visibility of desired color-distinguishablestructures, such as blood vessels, in color images recorded by an imagesensor of a videoscope.

SUMMARY OF THE DISCLOSURE

According to a first aspect, the present disclosure relates to a methodof enhancing the visibility of blood vessels in a color image capturedby an image capturing device of a medical device, said color imagehaving a plurality of color channels and having a plurality of pixels,wherein said method comprises for at least some of said plurality ofpixels the steps of: (a) processing data obtained from a first colorchannel together with data obtained from a second color channel todetermine a value of a first parameter indicative of the intensity inthe red spectrum relative to the total intensity of said pixel; and (b)using said value of said first parameter and a first value of a userparameter to alter said pixel, the first value of the user parameterbeing based on user input, and wherein the strength of the alteration isdependent on both the value of said first parameter and the first valueof said user parameter.

Consequently, a user may control the strength of the enhancement toadapt the enhancement to a specific situation. Furthermore, by usinginformation from at least two color channels more information in thecolor image may be used to estimate the location of the blood vesselsallowing a more precise estimate.

In some embodiments, the user parameter has at least three possiblevalue e.g. the user may select ‘low’ enhancement, ‘medium’ enhancementand ‘high’ enhancement. The user parameter may have more than threepossible values, whereby the user may select the strength of theenhancement on a sliding scale with ‘low’ enhancement at one end of thescale and ‘high’ enhancement at another end of the scale.

The user input may be an input from one or more buttons provided inconnection with the medical device e.g. if the medical device is anendoscope, the user input may be from one or more buttons arranged inconnection with the endoscope handle e.g. on the endoscope handle. As anexample, the endoscope handle may be provided with a first button forincreasing the strength of the enhancement and a second button fordecreasing the strength of the enhancement. Alternatively, the endoscopehandle may be provided with a single button for selecting the strengthof the enhancement e.g. a first activation of the button may select‘low’ enhancement, a second activation may select ‘medium’ enhancement,a third activation may select ‘high’ enhancement, and a fourthactivation may again select ‘low’ enhancement and so forth. A button ofthe one or more buttons may be used to activate/deactivate theenhancement e.g. if only a single button is provided the single buttonmay also activate/deactivate the enhancement.

The user input may alternatively/additionally be an input from one ormore buttons provided in connection with a monitor for displaying imagesobtained by the image capturing device. The one or more buttons may bearranged in proximity of the screen of the monitor e.g. at the displayframe.

Additionally/alternatively the screen of the monitor may be atouch-screen whereby the user input may be an input from thetouch-screen e.g. a virtual button on the touch-screen and/or a slideron the. The monitor may be configured to be in a first state and asecond state where when the monitor is in the first state thetouch-screen displays a first user interface allowing the user to turnon the enhancement and/or change the strength of the enhancement, andwhen the monitor is in the second state display a second user interfaceallowing the user to alter other imaging parameter and/or use a largerportion of the display surface for displaying live images.

In some embodiments, whenever the enhancement is activated a visualidentifier such as a symbol or icon is inserted into the enhanced imageto show that the image has been enhanced.

In some embodiment, the method further comprises storing a firstenhanced image; storing an original un-enhanced image or image datacapable of re-creating the original un-enhanced image based on thestored enhanced image; obtaining a second value of the user parameterbased on user input; and creating a second enhanced image based on theoriginal un-enhanced image and the second value of the user parameter,the second enhanced image being enhanced with a different strength thanthe first enhanced image.

Consequently, a user may turn off the enhancement on a captured andstored image and/or change the strength of the enhancement.

The user input may be received from one or more buttons on the medicaldevice and/or on a monitor. The first enhanced image and the originalun-enhanced image may be stored responsive to an activation of ashutter-release button e.g. on the medical device or on a monitor. Theimage data capable of re-creating the original un-enhanced image may bea difference image e.g. obtained by subtracting the enhanced image fromthe original image and/or a compressed image.

In some embodiments, said first parameter has at least three possiblevalues.

Consequently, by using a non-binary value to determine the degree ofalterations a more robust method is provided creating more life-likeimages.

The medical device may be a medical device adapted to be introduced intoa body cavity such as the body cavities of the digestive system or abody cavity of the airways. The medical device may be an elongated rigidor flexible endoscope, a capsule endoscope or laryngoscope. The medicaldevice may comprise one or more light sources configured to emitsubstantially white light. The medical device may be a single useelongated flexible endoscope. The image capturing device may be arrangedat a distal portion of an endoscope e.g. at the tip of an endoscope. Theimage capturing device may be operatively connectable to an imageprocessor configured to process the image data.Alternatively/additionally, the medical device may comprise an imageprocessor configured to process the image data. The color images may becoded in any color space such as an RGB type color space or an YCbCrtype color space. The color images may comprise at least three colorchannels. The steps of the method e.g. step (a) and step (b) may beperformed on the pixels of the color images in parallel e.g. step (a)may be performed for all pixels in the image and then subsequently step(b) may be performed for all pixels in the image. Alternatively, thesteps of the method may be performed sequential e.g. step (a) and step(b) may be performed on the pixels of the color images sequential e.g.step (a) and (b) may be performed on a first pixel and then subsequentstep (a) and (b) may be performed on a second pixel and so forth.Estimating a value of a first parameter indicative of the intensity inthe red spectrum relative to the total intensity has shown to be a goodindicator of blood vessels. The value may be a more precise indicator ofthe intensity in the red spectrum relative to the total intensity ifinformation from all color channels are used, however the value may alsobe determined using only information from only some color channels e.g.two out of three color channels.

In some embodiments, step (a) comprises: processing data obtained from afirst color channel together with data obtained from a second colorchannel and data obtained from a third color channel to determine avalue of said first parameter.

Consequently, by using more data a more precise estimate of the locationof the blood vessels may be provided.

In some embodiments, said data obtained from the first color channel isprocessed together with said data obtained from the second color channelto create a value of a first sub parameter, said data obtained from saidfirst color channel is processed together with said data obtained fromsaid third color channel to create a value of a second sub parameter,and wherein said value of said first sub parameter is processed togetherwith said value of said second sub parameter to create said value ofsaid first parameter.

In some embodiments, said value of said first parameter is created bycalculating an average of said value of the first sub parameter and thevalue of the second sub parameter.

The average may be a weighted average or an unweighted average.

In some embodiments, step (a) comprises subtracting said data obtainedfrom the second color channel from said data obtained from the firstcolor channel.

As an example, if the first color channel represents red and the secondcolor channel represents green then a large output will result when thered component of the pixel is significantly higher than the greencomponent.

Consequently, a simple way of determining a value of a parameterindicative of the intensity in the red spectrum relative to the totalintensity of the pixel is provided.

In some embodiments, the first parameter may have at least 8 possiblevalues, 16 possible values or 32 possible values.

Consequently, the alteration of the image may be done effectivelywithout introducing unnatural high frequency elements.

In some embodiments, both said value of said first sub parameter andsaid value of said second sub parameter are indicative of the intensityin the red spectrum relative to the total intensity of said pixel.

In some embodiments, said value of said first sub parameter is createdby subtracting said data obtained from the second color channel fromsaid data obtained from the first color channel, and wherein said valueof said second sub parameter is created by subtracting said dataobtained from the third color channel from said data obtained from thefirst color channel.

As an example, if the first color channel represents red, the secondcolor channel represents green, and the third color channel representsblue then the value of both the first sub parameter and the second subparameter will be large when the red component of the pixel issignificantly higher than both the green component and the bluecomponent.

The value of the first parameter may also be determined by calculating aratio between the data obtained from the first color channel and the sumof the data obtained from the first color channel, the second colorchannel and/or the third color channel e.g. by dividing the dataobtained from the first color channel with the sum of the data obtainedfrom the first color channel, the second color channel and/or the thirdcolor channel.

In some embodiments, parts of the color image having no blood vesselsare substantially unaltered and displayed with normal colors.

In some embodiments, step (b) comprises subtracting or adding a value ofan alteration parameter from the value of at least one color channel ofthe plurality of color channels of said color image, wherein the valueof the alteration parameter is related to the value of the firstparameter.

The value of the alteration parameter may simply be the value of thefirst parameter. The alteration parameter may be subtracted from allcolor channels of said color image.

In some embodiments, said method further comprises determining a valueof a second parameter indicative of the intensity of said pixel andwherein said value of said first parameter together with said value ofsaid second parameter is used to alter said pixel.

This may allow the method to decrease the strength of the alterations indark areas of the color image, where noise may make it difficult toprecisely determine blood vessel locations.

In some embodiments, said plurality of color channels are normalizedprior to being processed together.

In some embodiments, a low pass filtered image is created for each ofsaid plurality of color channels indicating a local average for eachpixel, and wherein each color channel is normalized using its low passfiltered image.

In some embodiments, said color image is an RGB color image said firstcolor channel being the red color channel and said second color channelbeing the green or blue color channel.

In some embodiments, said medical device is configured to be insertedinto a body cavity and illuminate said body cavity with white light whensaid color image is being recorded.

In some embodiments, said medical device is an endoscope.

In some embodiments, a high value of the first parameter indicates ahigh intensity in the red spectrum relative to the total intensity ofsaid pixel and a low value of the first parameter indicates a lowintensity in the red spectrum relative to the total intensity of saidpixel.

In some embodiments, values of the first parameter that are among the50% highest of all possible values results in alterations that are moresignificant than the alterations that results from values of the firstparameter that are among the 50% lowest of all possible values.

In some embodiments, for at least 50% of the possible values of saidfirst parameter an increase in the value of the first parameter resultsin an increase in the strength of the alteration.

In some embodiments, the alteration of said pixel is independent of theintensity in the green spectrum relative to the blue spectrum.

According to a second aspect, the present disclosure relates to an imageprocessor for enhancing the visibility of blood vessels in a colorimage, said image processor comprising a processing unit operationallyconnectable to an image capturing device of a medical device, whereinsaid processing unit is configured to receive a color image having aplurality of color channels from said image capturing device, said colorimage has a plurality of pixels, and said processing unit further isconfigured to for at least some of said plurality of pixels (a) processdata obtained from a first color channel together with data obtainedfrom a second color channel to determine a value of a first parameterindicative of the intensity in the red spectrum relative to the totalintensity of said pixel; and (b) using said value of said firstparameter and a first value of a user parameter to alter said pixel, thefirst value of the user parameter being based on user input, and whereinthe strength of the alteration is dependent on both the value of saidfirst parameter and the first value of said user parameter.

In some embodiments, the user parameter has at least three possiblevalue e.g. the user may select ‘low’ enhancement, ‘medium’ enhancementand ‘high’ enhancement. The user parameter may have more than threepossible values, whereby the user may select the strength of theenhancement on a sliding scale with ‘low’ enhancement at one end of thescale and ‘high’ enhancement at another end of the scale.

The user input may be an input from one or more buttons operationallyconnectable to the processing unit provided in connection with themedical device e.g. if the medical device is an endoscope, the userinput may be from one or more buttons arranged in connection with theendoscope handle e.g. on the endoscope handle. As an example, theendoscope handle may be provided with a first button for increasing thestrength of the enhancement and a second button for decreasing thestrength of the enhancement. Alternatively, the endoscope handle may beprovided with a single button for selecting the strength of theenhancement e.g. a first activation of the button may select ‘low’enhancement, a second activation may select ‘medium’ enhancement, athird activation may select ‘high’ enhancement, and a fourth activationmay again select ‘low’ enhancement and so forth. A button of the one ormore buttons may be used to activate/deactivate the enhancement e.g. ifonly a single button is provided the single button may alsoactivate/deactivate the enhancement.

The user input may alternatively/additionally be an input from one ormore buttons operationally connectable to the processing unit providedin connection with a monitor for displaying images obtained by the imagecapturing device. The image processor may be part of the monitor orconnectable to the monitor. The one or more buttons may be arranged inproximity of the screen of the monitor e.g. at the display frame.

Alternatively/additionally the screen of the monitor may be atouch-screen operationally connectable to the processing unit wherebythe user input may be an input from the touch-screen e.g. a virtualbutton on the touch-screen and/or a slider on the touch-screen or thelike. The monitor may be configured to be set in a first state and asecond state where when the monitor is in the first state thetouch-screen displays a first user interface allowing the user to turnon the enhancement and/or change the strength of the enhancement, andwhen the monitor is in the second state display a second user interfaceallowing the user to alter other imaging parameter and/or use a largerportion of the display surface for displaying live images.

In some embodiments, the processing unit is further configured to inserta visual identifier such as a symbol or icon is inserted into theenhanced image to show to the user that the image has been enhanced whenthe enhanced image is displayed.

In some embodiment, the processing unit is operationally connectable toa storage unit and further configured to store on the storage unit afirst enhanced image; store on the storage unit an original un-enhancedimage or image data capable of re-creating the original un-enhancedimage based on the stored enhanced image; obtained a second value of auser parameter based on user input; and create a second enhanced imagebased on the original un-enhanced image and the second value of the userparameter, the second enhanced image being enhanced with a differentstrength than the first enhanced image.

Consequently, a user may change the strength of the enhancement onrecorded images.

The user input may be received from one or more buttons on the medicaldevice and/or on a monitor operationally connectable to the processingunit. The processing unit may be configured to store the first enhancedimage and the original un-enhanced image responsive to an activation ofa shutter-release button e.g. on the medical device or on a monitor. Theprocessing unit may be operationally connectable to a monitor andconfigured to allow a user to control the monitor to display the firstenhanced image, the second enhanced image, or the original un-enhancedimage. The image data capable of re-creating the original un-enhancedimage may be a difference image obtained by subtracting the enhancedimage from the original image or vice versa and/or a compressed image.

In some embodiments, said first parameter has at least three possiblevalues.

In some embodiments, step (a) comprises: processing data obtained from afirst color channel together with data obtained from a second colorchannel and data obtained from a third color channel to determine avalue of said first parameter.

In some embodiments, said data obtained from the first color channel isprocessed together with said data obtained from the second color channelto create a value of a first sub parameter, said data obtained from saidfirst color channel is processed together with said data obtained fromsaid third color channel to create a value of a second sub parameter,and wherein said value of said first sub parameter is processed togetherwith said value of said second sub parameter to create said value ofsaid first parameter.

In some embodiments, said value of said first parameter is created bycalculating an average of said value of the first sub parameter and thevalue of the second sub parameter.

In some embodiments step (a) comprises subtracting said data obtainedfrom the second color channel from said data obtained from the firstcolor channel.

In some embodiments, the first parameter may have at least 8 possiblevalues, 16 possible values or 32 possible values.

In some embodiments, both said value of said first sub parameter andsaid value of said second sub parameter are indicative of the intensityin the red spectrum relative to the total intensity of said pixel.

In some embodiments, said value of said first sub parameter is createdby subtracting said data obtained from the second color channel fromsaid data obtained from the first color channel, and wherein said valueof said second sub parameter is created by subtracting said dataobtained from the third color channel from said data obtained from thefirst color channel.

In some embodiments, parts of the color image having no blood vesselsare substantially unaltered and displayed with normal colors.

In some embodiments, step (b) comprises subtracting or adding a value ofan alteration parameter from the value of at least one color channel ofthe plurality of color channels of said color image, wherein the valueof the alteration parameter is related to the value of the firstparameter.

In some embodiments, said processing unit is further configured to:determine a value of a second parameter indicative of the intensity ofsaid pixel and wherein said value of said first parameter together withsaid value of said second parameter are used to alter said pixel.

In some embodiments, said plurality of color channels are normalizedprior to being processed together.

In some embodiments, a low pass filtered image is created for each ofsaid plurality of color channels indicate a local average for eachpixel, and wherein each color channel is normalized using its low passfiltered image.

In some embodiments, said value of said first sub parameter is createdby subtracting said data obtained from the second color channel fromsaid data obtained from the first color channel, and wherein said valueof said second sub parameter is created by subtracting said dataobtained from the third color channel from said data obtained from thefirst color channel.

In some embodiments, said color image is a RGB color image said firstcolor channel being the red color channel and said second color channelbeing the green or blue color channel.

In some embodiments, said medical device is configured to be insertedinto a body cavity and illuminate said body cavity with white light whensaid color images are being recorded.

In some embodiments, said medical device is an endoscope.

In some embodiments, a high value of the first parameter indicates ahigh intensity in the red spectrum relative to the total intensity ofsaid pixel and a low value of the first parameter indicates a lowintensity in the red spectrum relative to the total intensity of saidpixel.

In some embodiments, values of the first parameter that are among the50% highest of all possible values results in alterations that are moresignificant than the alterations that results from values of the firstparameter that are among the 50% lowest of all possible values.

In some embodiments, for at least 50% of the possible values of saidfirst parameter an increase in the value of the first parameter resultsin an increase in the strength of the alteration.

In some embodiments, the alteration of said pixel is independent of theintensity in the green spectrum relative to the blue spectrum.

According to a third aspect the present disclosure relates to an imageprocessor for identifying potential pathological vascular structures,said image processor comprising a processing unit operationallyconnectable to an image capturing device of a medical device, whereinsaid processing unit is configured to process an image adapted forcomputer image analysis using a machine learning data architecturetrained to identify potential pathological vascular structures in suchimages, wherein said image adapted for computer analysis is generated byprocessing a color image having a plurality of color channels recordedby said image capturing device, said color image has a plurality ofpixels wherein the processing of said color image comprises for at leastsome of said plurality of pixels (a) process data obtained from a firstcolor channel together with data obtained from a second color channel todetermine a value of a first parameter indicative of the intensity inthe red spectrum relative to the total intensity of said pixel; and (b)using said value of said first parameter to create a pixel value of theimage adapted for computer image analysis.

Consequently, by pre-processing the color images using steps a) and b)the vascular structures may be enhanced making it easier for the machinelearning data architecture to identify potential pathological vascularstructures. This may both enable the machine learning data architectureto identify more potential pathological vascular structures and performits processing faster, i.e. using fewer computational resources enablingreal time analysis by the machine learning data architecture.

In some embodiments, said machine learning data architecture is asupervised machine learning architecture, trained by being provided witha training data set of images created by steps a) and b), where a firstsubset of images of said training data set show a pathological vascularstructure and a second subset of images of said training data set show ahealthy vascular structure.

In some embodiments, the training data set comprises a plurality ofimages showing vascular structures of tumours.

The plurality of images may be recorded by an image capturing device ofa medical device such as an endoscope.

In some embodiments, the pixel values of the image adapted for computerimage analysis corresponds to the value of the first parameteroptionally multiplied with a weight value derived from said color image;or the pixel values of the image adapted for computer image analysis isan altered pixel from said color image altered using the value of saidfirst parameter and wherein the strength of the alteration is dependenton the value of said first parameter.

In some embodiments, said data obtained from the first color channel isprocessed together with said data obtained from the second color channelto create a value of a first sub parameter, said data obtained from saidfirst color channel is processed together with said data obtained fromsaid third color channel to create a value of a second sub parameter,and wherein said value of said first sub parameter is processed togetherwith said value of said second sub parameter to create said value ofsaid first parameter.

In some embodiments, said value of said first parameter is created bycalculating an average of said value of the first sub parameter and thevalue of the second sub parameter.

In some embodiments step (a) comprises subtracting said data obtainedfrom the second color channel from said data obtained from the firstcolor channel.

In some embodiments, the first parameter may have at least 8 possiblevalues, 16 possible values or 32 possible values.

In some embodiments, both said value of said first sub parameter andsaid value of said second sub parameter are indicative of the intensityin the red spectrum relative to the total intensity of said pixel.

In some embodiments, said value of said first sub parameter is createdby subtracting said data obtained from the second color channel fromsaid data obtained from the first color channel, and wherein said valueof said second sub parameter is created by subtracting said dataobtained from the third color channel from said data obtained from thefirst color channel.

In some embodiments, said processing unit is further configured to:determine a value of a second parameter indicative of the intensity ofsaid pixel and wherein said value of said first parameter together withsaid value of said second parameter are used to create said pixel valueof the image adapted for computer image analysis.

In some embodiments, said plurality of color channels are normalizedprior to being processed together.

In some embodiments, a low pass filtered image is created for each ofsaid plurality of color channels indicate a local average for eachpixel, and wherein each color channel is normalized using its low passfiltered image.

In some embodiments, said value of said first sub parameter is createdby subtracting said data obtained from the second color channel fromsaid data obtained from the first color channel, and wherein said valueof said second sub parameter is created by subtracting said dataobtained from the third color channel from said data obtained from thefirst color channel.

In some embodiments, said color image is a RGB color image said firstcolor channel being the red color channel and said second color channelbeing the green or blue color channel.

In some embodiments, a high value of the first parameter indicates ahigh intensity in the red spectrum relative to the total intensity ofsaid pixel and a low value of the first parameter indicates a lowintensity in the red spectrum relative to the total intensity of saidpixel.

In some embodiments, values of the first parameter that are among the50% highest of all possible values results in alterations that are moresignificant than the alterations that results from values of the firstparameter that are among the 50% lowest of all possible values.

In some embodiments, for at least 50% of the possible values of saidfirst parameter an increase in the value of the first parameter resultsin an increase in the strength of the alteration.

In some embodiments, the alteration of said pixel is independent of theintensity in the green spectrum relative to the blue spectrum.

In some embodiments, the machine learning data architecture is anartificial neural network such as a deep structured learningarchitecture.

In some embodiments, the processing unit is directly operationallyconnectable to the image capturing device and configured to receive thecolor image and perform steps a) and b) to create the image adapted forcomputer image analysis.

In some embodiments, the processing unit is indirectly operationallyconnectable to the image capturing device via another image processor.

In some embodiments, said image processor is configured to receive saidimage adapted for computer image analysis from said another imageprocessor, said another image processor being configured to receive thecolor image and perform steps a) and b) to create the image adapted forcomputer image analysis.

According to a fourth aspect, the present disclosure relates to amonitor for displaying images obtained by an image capturing device of amedical device, wherein said monitor comprises an image processor asdisclosed in relation to the second aspect of the present disclosure orthe third aspect of the present disclosure.

According to a fifth aspect, the present disclosure relates to anendoscope system comprising an endoscope and an image processor asdisclosed in relation to the second aspect of the present disclosure orthe third aspect of the present disclosure, wherein said endoscope hasan image capturing device and said processing unit of said imageprocessor is operationally connectable to said image capturing device ofsaid endoscope.

In some embodiments, the endoscope system further comprises a monitor asdisclosed in relation to the fourth aspect of the present disclosure,wherein said monitor is operationally connectable to said imagecapturing device of said endoscope and configured display said capturedimages.

According to a sixth aspect the present disclosure relates to a computerprogram product comprising program code means adapted to cause a dataprocessing system to perform the steps of the method disclosed inrelation to the first aspect of the present disclosure, when saidprogram code means are executed on the data processing system.

In some embodiments, said computer program product comprises anon-transitory computer-readable medium having stored thereon theprogram code means.

According to a seventh aspect the present disclosure relates to a dataprocessing system configured to perform the method disclosed in relationto the first aspect of the present disclosure.

The different aspects of the present disclosure can be implemented indifferent ways including methods, image processors, monitors, endoscopesystems, and compute program products described above and in thefollowing, each yielding one or more of the benefits and advantagesdescribed in connection with at least one of the aspects describedabove, and each having one or more preferred embodiments correspondingto the preferred embodiments described in connection with at least oneof the aspects described above and/or disclosed in the dependant claims.Furthermore, it will be appreciated that embodiments described inconnection with one of the aspects described herein may equally beapplied to the other aspects.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and/or additional objects, features and advantages of thepresent disclosure, will be further elucidated by the followingillustrative and non-limiting detailed description of embodiments of thepresent disclosure, with reference to the appended drawings, wherein:

FIG. 1 shows an example of an endoscope;

FIG. 2 shows an example of a monitor that can be connected to theendoscope shown in FIG. 1;

FIG. 3 shows a flow chart of a method of enhancing the visibility ofblood vessels in a color image captured by an image capturing device ofa medical device according to an embodiment of the disclosure;

FIG. 4 shows a schematic drawing of an endoscope system according to anembodiment of the present disclosure;

FIG. 5 shows a schematic drawing of an endoscope system according to anembodiment of the present disclosure;

FIG. 6 shows a flow chart of a method of enhancing the visibility ofblood vessels in a color image captured by an image capturing device ofa medical device according to an embodiment of the disclosure;

FIG. 7 shows a flow chart of a method of enhancing the visibility ofblood vessels in a color image captured by an image capturing device ofa medical device according to an embodiment of the disclosure;

FIG. 8a shows a color image of an internal cavity before the visibilityof the blood vessels have been enhanced and FIG. 8b shows the colorimage after the visibility of the blood vessels have been enhancedaccording to an embodiment of the disclosure;

FIG. 9 shows a schematic drawing of a visualization system according toan embodiment of the disclosure;

FIG. 10 illustrates how the strength of the enhancement may becontrolled using a touch-screen according to an embodiment of thedisclosure;

FIG. 11 shows a flow chart of a method of enhancing the visibility ofblood vessels in a color image captured by an image capturing device ofa medical device according to an embodiment of the disclosure; and

FIG. 12 shows a flow chart of a method according to an embodiment of thedisclosure.

In the drawings, corresponding reference characters indicatecorresponding parts, functions, and features throughout the severalviews. The drawings are not necessarily to scale and certain featuresmay be exaggerated in order to better illustrate and explain thedisclosed embodiments.

DETAILED DESCRIPTION

In the following description, reference is made to the accompanyingfigures, which show by way of illustration how the embodiments of thepresent disclosure may be practiced.

Due to the blood light absorption spectrum, blood vessels are morevisible in the green and blue components of an RGB image than in the redcomponent. When it is desired to highlight the blood vessels, thischaracteristic of blood vessels can be used to create, from a baseimage, a differentiated mass image (e.g. first parameter image) in whichthe pixels related to the blood vessels, or other structures ofinterest, stand out relative to the remaining pixels. The differentiatedmass image is then combined with the base image to produce an enhancedimage in which the blood vessels are darkened relative to the remainingparts of the image.

The differentiated mass image can be generated by processing the red andgreen components, or the red and blue components, or the red, green andblue components of the color image. Processing all three components ispreferrable since the green and blue components provide differentinformation about the blood vessels. It should be understood that theterm “mass” refers to a color differentiable mass. Blood vessels are oneexample of a color differentiable mass. Other examples include bones,scar tissue, organs, foreign objects, etc. The steps to create thedifferentiated mass image might differ depending on the colorcharacteristics of the color differentiable mass. Thus, the descriptionsbelow made with reference to blood vessels are to illustrate thedisclosed image processing methods, which are generally applicable toother types of mass.

The base image can be an original image or an original image that wasprocessed in traditional ways to improve contrast, white balance etc.The original image may be generated by an image sensor including a Bayerfilter, in which, as is well known, the filter pattern is 50% green, 25%red, and 25% blue.

Various additional steps can be taken to further improve the display ofthe blood vessels. In one example, the impact of the red pixels isreduced. The reduction can be accomplished by normalizing the colorcomponents, by reducing the intensities of the red pixels, or in othersuitable ways. Normalization may be accomplished by low-pass filteringto create low-pass filtered images and then dividing the images by thelow-pass filtered images. Reducing the intensities can be accomplishedby applying a negative gain to the red pixels or by subtracting aconstant value from the red pixels. Red impact reduction may beperformed prior to generating the differentiated mass image.

In another example, the impact of the pixels that contain little or noinformation is reduced. The reduction can be accomplished by setting theintensity of pixels with high (overexposed) or low (underexposed)intensities to 0. Underexposed pixels may reflect tissue far from thetip of the endoscope, thus poorly illuminated. Overexposed pixels mayreflect tissue near the light of the endoscope. One way to reduce theimpact is to create a mask image by binarizing the pixels. Pixels withintensity in a desired range are assigned a value of 1 and pixels in theundesired intensity range are assigned a value of 0. When the mask imageis multiplied by another image, the intensities of the pixels with valueof 0 remove the noise provided by the under and over exposed pixels. Ifthe intensities of the pixels range between −1 and +1, for example, asthey might in the differentiated mass image, pixels with negativeintensities reflect dark areas of the image and their impact is reducedby creating a mask with the positive intensity pixels. The over/underexposure impact can be reduced before or after creating thedifferentiated mass image.

In a further example, a user may determine the level of enhancement. Thelevel can be selected by the user with an enhancement level selector,and a user selected enhancement amount can then be applied. One way toapply the user selected enhancement amount is to apply a gain value toan image. The image may be the differentiated mass image, before orafter application of a mask. The gain value multiplies the intensitiesof all the pixels by the gain amount. The gain may be in a range between0-1, where 0 indicates no gain and values between 0-1 indicate anincrease of the enhancement up to a maximum value that can be based onthe particular videoscope or preset.

In the figures below, detailed embodiments depicting the generation ofenhanced images to highlight color differentiable masses are provided.FIGS. 1, 2, 4, 5, and 9 depict embodiments of a visualization systemconfigured to implement the image enhancement method. FIGS. 3, 6 and 7disclose detailed embodiments of the image enhancement method. FIGS. 8aand 8b contrast an unenhanced image with an enhanced image. FIG. 10contrasts an un-enhanced image with images enhanced at low, medium, andhigh enhancement levels selected by the user. FIGS. 11 and 12 discloseembodiments of methods to leverage the enhanced images to identify amass or structure of interest.

FIG. 1 illustrates an example of an endoscope 100. This endoscope may beadapted for single-use. The endoscope 100 is provided with a handle 102attached to an insertion tube 104 provided with a bending section 106.The insertion tube 104 as well as the bending section 106 may beprovided with one or several working channels such that instruments,such as a gripping device, may be inserted into a human body via theendoscope. One or several exit holes of the one or several channels maybe provided in a tip part, or cap, 108 of the endoscope 100. In additionto the exit holes, a camera 109 and one or several light sources, suchas light emitting diodes (LEDs), fiber, or any other light emittingdevices, may be placed in the tip part 108. The camera may comprise animage sensor, such as a CMOS sensor or any other image capturing device,and one or more lenses defining a field of view of the camera.

The bending section 106 can be bent in different directions with respectto the insertion tube 104 to make it possible for the operator toredirect the camera and obtain different views. The operator can controlthe bending section 106 with a knob 110 placed on the handle 102. Thehandle is designed so that the knob 110 can be actuated by a thumb ofthe operator, but other actuation designs to orient the field of view ofthe camera are also possible. A push button 112 may be used to control agripping device or other device provided via a working channel. Thehandle is designed such that the push button 112 can be actuated by afinger of the operator holding the handle, but other tool actuatordesigns are also possible.

The image data captured by the camera and, optionally, other datacaptured by other sensors, can be transferred via a cable 114 having aconnector 116 to a monitor 200, shown in FIG. 2. Even though wire-baseddata transmission is illustrated, it is equally possible to transferimage data by using a wireless transceiver supported by the endoscope.

An embodiment of a enhancement level selector 118 is shown in schematicform on handle 102. The enhancement level selector will be described inmore detail with reference to FIGS. 4 and 5. Generally, the enhancementlevel selector is an actuator, virtual or physical, operable by the userto generate a signal indicative of a desired mass enhancement level. Inone variation, the enhancement level selector includes one or morebuttons configured to enable the user to select the video enhancementlevel. In one example, an enhancement level selector positioned in thehandle may include a potentiometer operable by the user to change aresistance indicative of the level of enhancement desired by the user.In another example, an enhancement level selector positioned in thehandle may include a potentiometer operable by the user to change aresistance indicative of the level of enhancement desired by the user,and an I²C slave node circuit that includes the ADC and transmits acorresponding value via an existing I²C channel to the monitor, where anI²C master communicates the value of the user parameter to the GUI.

FIG. 2 illustrates an example of a portable monitor 200 including adisplay screen 202 and a communication port 204 operable to receive theconnector 116 of the endoscope 100 to establish communications betweenthe portable monitor 200 and the endoscope 100. The monitor 200 isconfigured to display images based with the display screen 202 of imagedata captured by the camera 109 of the endoscope 100. An operator of theendoscope 100 is able to see and analyze an inside of the human body to,for instance, localize a position for taking a sample. In addition, theoperator will be able to control the instrument in a precise manner dueto the visual feedback made available by the camera 109 and the monitor200. Further, since some diseases or health issues may result in a shiftin natural colors or other visual symptoms, the visual feedback providesthe operator valuable input for making a diagnosis based on the imagedata provided via the camera sensor and the monitor.

The monitor 200 is preferably a re-usable piece of equipment. By havingone single-use piece of equipment and another re-usable piece ofequipment, most of the data processing capability may be placed in there-usable piece of equipment in order to reach a cost efficient level atthe same time as being safe to use from a health perspective. Single-usedevices are not made to withstand sterilization and designconsiderations include low cost and disposability.

The monitor 200 may comprise an image processor as explained in relationto the second aspect of the disclosure and/or the third aspect of thedisclosure. The monitor 200 may be provided with a enhancement levelselector 206 described in more detail with reference to FIG. 4. Theenhancement level selector 206 may comprise an icon of a graphical userinterface (GUI) which the user may actuate to select the desiredenhancement level. In other variations, the enhancement level selector206 may include one or more physical buttons, located on a marginsurrounding the display screen or on a side of the monitor, configuredto enable a user to select the enhancement level.

As indicated above, the video enhancement highlights masses, orstructures, of particular colors. FIG. 3 shows a flowchart of anembodiment of a method for enhancing the visibility of blood vessels ina color image. It should be understood that a color image in thiscontext is comprised of data corresponding to color channels orcomponents. When each color channel is split from the color image, thedata can be referred to as a red, green, or blue color image, which isrepresented by an array comprising pixel data including the respectivecolor information. The method comprises, for at least some of theplurality of pixels, at 301, processing data obtained from a first colorchannel together with data obtained from a second color channel todetermine a value of a first parameter indicative of the intensity inthe red spectrum relative to the total intensity of a pixel. At 302, themethod continues by using the value of the first parameter to enhancethe pixel. The first parameter has at least three possible values, andthe strength of the enhancement is dependent on the value of the firstparameter.

The first parameters of the pixels form a first image, which may thedifferentiated mass image. Processing data obtained from a first colorchannel together with data obtained from a second color channel todetermine a value of a first parameter may comprise obtaining adifference between the red and green, red and blue, or both red/greenand red/blue channels. Processing may also comprise reducing the impactof the red pixels, as discussed above, before generating the first, ordifferentiated mass, image, and neutralizing the impact of over andunder exposed pixels. If a user selected enhancement level is applied,processing may also comprise taking the selected enhancement level intoaccount when reducing the impact of the red pixels, for example byreducing the impact more or less depending on the selected enhancementlevel. The intensity of the processed image can be adjusted to completethe enhanced image, therefore changing the relative intensity of the redpixels to the green or blue or both green and blue pixel intensitieschanges how dark the blood vessels will appear.

FIG. 4 shows a schematic drawing of an embodiment of an endoscopesystem, denoted by numeral 401, comprising an endoscope 402communicatively coupled to a monitor 410. The endoscope 402 includes acamera 403 and an enhancement level selector 404. The monitor 410includes an image processor 412, as disclosed in relation to the secondaspect of the disclosure and/or the third aspect of the disclosure, anda enhancement level selector 414. The camera 403 is operationallyconnectable to the image processor 412, which is configured to receive avideo enhancement signal resulting from actuation of the enhancementlevel selectors and to enhance the video based on the signal. In thisembodiment, the image processor 412 is integrated in the monitor 410,which includes a display screen configured to display the enhancedimages. The video enhancement signal represents a value of a userparameter, or second parameter, for controlling the strength of theenhancements. One or the other of the enhancement level selectors may beomitted. The enhancement level selector 404 may be identical to theenhancement level selector 118 and the enhancement level selector 414may be identical to the enhancement level selector 206.

FIG. 5 shows another embodiment of an endoscope system, denoted bynumeral 501, including the endoscope 402 and the image processor 412, asdisclosed in relation to the second aspect of the disclosure and/or thethird aspect of the disclosure. The endoscope system 501 differs fromthe endoscope system 401 in that the image processor 412 is notintegrated with the monitor, depicted by numeral 510. Instead, the imageprocessor 412 is contained in a housing 502. The image processor 412 maycomprise processing instructions, illustratively image processing logic504, and optionally hardware, described further below, to receive userinputs indicative of the enhancement level. The housing 502 includescommunication ports to receive the connector from the endoscope 402 andincludes a video output port to output video signals to display theimages with the display screen 512 of the monitor 510. The video outputport may be an HDMI port.

The GUI may be provided by GUI logic. The GUI logic may includeinstructions to generate the enhancement level control, e.g. a selectorof a value of a user parameter. Where the images are displayed in adisplay screen of a monitor, such as a portable monitor with atouch-screen, the user may engage the GUI by touch. The GUI may presentin a first panel on the display screen a small version of live imagesprovided by a first videoscope and in a second panel a large version ofthe live images provided by a second videoscope. A third panel may beprovided in which the GUI may present various icons/control objectscorresponding to actions selectable by the user with any of theabove-described user input devices, to for example store a copy of alive image, store a portion of video corresponding to live images,invert the views, turn the enhancement features on and off, and selectthe level of enhancement.

Where the images are displayed in the image processor that does notinclude a display screen, for example, the image processor may include auser interface such as a wireless interface operable to receive userinputs via a mouse, keyboard, or other physical user input devices.Example wireless interfaces include Bluetooth and Zigbee controllers.The user interface may also comprise a USB port to receive a USBconnector including the wireless interface or a USB connector of a wireduser input device. Thus, the image processor provides for flexibility inreceiving user inputs via various user input devices, regardless whethera display screen is integrated therewith. The term “logic” as usedherein includes software and/or firmware executing on one or moreprogrammable processing devices, application-specific integratedcircuits, field-programmable gate arrays, digital signal processors,hardwired logic, or combinations thereof. Therefore, in accordance withthe embodiments, various logic may be implemented in any appropriatefashion and would remain in accordance with the embodiments hereindisclosed. Logic may comprise processing instructions embedded innon-transitory machine-readable media (e.g. memory).

The image processor includes medical device interfaces includingconnectors operable to receive the plugs of the videoscope's cables andto receive image data therefrom as disclosed above with reference toFIGS. 4 and 5. Image data may be referred to as “live images” or “livevideo” if they are received substantially in real-time from thevideoscopes. The live video comprises a plurality of frames, each ofwhich can be referred to as an “image.” The image processor alsoincludes the GUI logic and processing logic configured to implement theimage enhancement methods described herein.

FIG. 6 shows a flowchart of an embodiment of a method of enhancing thevisibility of blood vessels in a color image captured by a camera of avideoscope, such as endoscopes 100, 402. The method may be performed bythe processing logic of the image processor. Shown is one color image601 having a plurality of color channels. In this embodiment the colorimage 601 is coded in a RGB color space. In the first step, the colorimage 601 is split in the red color channel 602, the green color channel603, and the blue color channel 604. One or more of the color channels602, 603, 604 may be normalized as described below. Preferrably, atleast the red color channel is normalized. Next for each pixel, a valueof a first sub parameter is created by subtracting 605 data obtainedfrom the green color channel 603 (e.g. the green intensity value) fromdata obtained from the red color channel 602 (e.g. the red intensityvalue). This results in a first sub parameter image 607.Correspondingly, for each pixel, a value of a second sub parameter iscreated by subtracting 606 data obtained from the blue color channel 604(e.g. the blue intensity value) from data obtained from the red colorchannel 602 (e.g. the red intensity value). This results in a second subparameter image 608. Then, for each pixel, a value of a first parameteris created by calculating an average 609 of the value of the first subparameter and the value of the second sub parameter. This results in afirst parameter image 610. The first parameter has at least threepossible values e.g. at least 8, 16, 32, 64, 128, 256 possible values.The first parameter image 610 shows regions in the color image 601 wherethe intensity in the red spectrum relative to the total intensity ishigh. This has shown to be a reliable indicator of blood vessels,because due to higher absorption of blue and green by the blood vessels,the total intensity in the area of the blood vessels is lower than insurrounding areas. Finally, the first parameter image 610 is subtractedfrom the base image to alter 611 the color image 601 creating an alteredor enhanced image 612, wherein the strength of the alteration isdependent on the value of the first parameter. Optionally, a value of auser parameter 613 may be used to control the strength of thealteration, i.e. so that the strength of the alteration is dependent onthe value of the first parameter and the value of the user parameter.

As an example, for each pixel, the value of the first parameter may besubtracted from the value of each color channel in the color image 601.This will have the effect that the blood vessels will become darker andthe remaining parts of the image will remain substantially unchanged orbecome slightly darker. However, the colors will be left substantiallyunaffected. The overall intensity of the altered image 612 may beadjusted so that the intensity of the areas of the altered image 612without blood vessels will have an intensity substantially matching theintensity of the corresponding areas in the original color image 601.For example, pixels having a small difference from the mean intensity ofthe first image (calibration pixels) could be considered to not haveblood vessels, and the average intensity of these pixels in the baseimage could be used to calibrate the intensity of the altered image,such that the intensity of the altered image is changed until theaverage intensity of the calibration pixels in the altered image matchesthe average in the base image. The value of the user parameter may be avalue between 0 and 1 that is used to scale the first parameter imagee.g. by multiplying the first parameter image with the value of the userparameter, and then use the scaled first parameter image to subtractfrom the value of each color channel in the color image 601 as describedabove.

FIG. 7 shows a flowchart of another embodiment of the method ofenhancing the visibility of blood vessels in a color image captured byan image capturing device of a medical device, e.g. a videoscope. Themethod may be performed by the processing logic of the image processor.The method may be performed by the processing logic of the imageprocessor. Shown is a single color image 701 having a plurality of colorchannels. In this embodiment the color image 701 is coded in a RGB colorspace. In the first step, the color image 701 is split in the red colorchannel 702, the green color channel 703, and the blue color channel704. Next, the red color channel 702 is low pass filtered 705 creating alow pass filtered red color channel 708, the green color channel 703 islow pass filtered 706 creating a low pass filtered green color channel709, and the blue color channel is low pass filtered 707 creating a lowpass filtered blue color channel 710. The low pass filtered colorchannels 708-710 show local averages for each pixel. Next, the low passfiltered red color channel 708 is used to normalize 711 the red colorchannel 702 creating a normalized red color channel 714, the low passfiltered green color channel 709 is used to normalize 712 the greencolor channel 703 creating a normalized green color channel 715, and thelow pass filtered blue color channel 710 is used to normalize 714 theblue color channel 704 creating a normalized blue color channel 716.Normalization may be performed by dividing the color channel by therespective low pass filtered color channel. For example, dividing thered component image by the red pass filtered red component image.

Then, the normalized color channels 714-716 are processed together 718to create a first parameter image 720 indicative of the intensity in thered spectrum relative to the total intensity. The normalized colorchannels 714-716 may be processed together 718 to create the firstparameter image 720 in the same way as the color channels 602-604 inFIG. 6 are processed together to create the first parameter image 610.Next, the red, green, and blue color channel 702-704 are processedtogether to determine a value of a second parameter indicative of theintensity of each pixel e.g. by summing the red, green, and blue colorchannel 702-704, creating a second parameter image 719. Next, the firstparameter image 720 and the second parameter image 719 are processedtogether 721 to create an alteration parameter image 722. This may bedone by per pixel multiplying the first parameter image 720 with thesecond parameter image 719. Finally, the alteration parameter image 722is used to alter 723 the color image 701 creating an altered or enhancedimage 724, wherein the strength of the alteration is dependent on thevalue of the alteration parameter image 722. In one variation, thealteration comprises subtracting the alteration parameter image 722 fromat least one color channel of the color image 701, preferrably the redchannel, creating an altered or enhanced image 724. In anothervariation, the alteration comprises subtracting the alteration parameterimage 722 from all three channel of the color image 701, creating analtered or enhanced image 724.

FIG. 8a shows a color image of an internal cavity before the visibilityof the blood vessels have been enhanced and FIG. 8b shows the colorimage after the visibility of the blood vessels have been enhancedaccording to an embodiment of the disclosure. It can be seen that theblood vessels are more clear in the image in FIG. 8b while thepresentation of the other tissue types are substantially unchanged. Thiswill allow the medical personnel to effectively examine both thevascular structures and the other areas of the internal cavity forpathological changes.

FIG. 9 shows a schematic drawing of an endoscope system 901 according toan embodiment of the disclosure. The endoscope system 901 comprises anendoscope 902, a first image processor 904, and a second image processor906, where both the first image processor 904 and the second imageprocessor 906 have a processing unit. The endoscope 902 has an imagecapturing device 903 and the processing unit of the first imageprocessor 904 is operationally connectable to the image capturing deviceof the endoscope 903. In this embodiment, the first image processor 904is integrated in a monitor 905 and the processing unit of the secondimage processor 906 is directly operationally connectable to theprocessing unit of the first image processor 904 and indirectlyoperationally connectable to the image capturing device of the endoscope903 via the first image processor 904. In this embodiment the processingunit of the first image processor 904 is configured to generate an imageadapted for computer image analysis by processing a color image having aplurality of color channels recorded by the image capturing device 903,the color image has a plurality of pixels wherein the processing of thecolor image comprises for at least some of said plurality of pixels thesteps of: (a) process data obtained from a first color channel togetherwith data obtained from a second color channel to determine a value of afirst parameter indicative of the intensity in the red spectrum relativeto the total intensity of said pixel; (b) using said value of said firstparameter to create a pixel value of the image adapted for computerimage analysis.

The image adapted for computer image analysis is forwarded to the secondimage processor 906 where the image adapted for computer analysis isprocessed using a machine learning data architecture trained to identifypotential pathological vascular structures in such images.Identification of pathological vascular structures is identified bycomparing image characteristics to a library of characteristicsidentified in training images.

The second image processing unit 906 may be arranged in proximity of thefirst image processor 904, where the first and second image processor904, 906 communicate directly or via a local network. Alternatively, thesecond image processor may be arranged remotely from the first imageprocessor and communicate via a WAN, such as the internet. The outputfrom the machine learning data architecture may be a notificationprovided to the first image processor 904. The notification may simplyspecify that a potential pathological vascular structure has beenidentified. However, the notification may also indicate the type ofpathology and/or the location in the image. If the notificationspecifies the location of the potential pathology, then the monitor 905may be configured to highlight the part of the image where the potentialpathology has been identified. The image adapted for computer analysismay more clearly show the vascular structures (compared to the originalcolor image) thereby making it easier for the machine learning dataarchitecture to identify potential pathological vascular structures.Examples of images adapted for computer analysis are (with reference tothe FIG. 7 embodiment) the altered image 724, the first parameter image720, and the alteration parameter image 722.

FIG. 10 illustrates how the strength of the enhancement may becontrolled using a touch-screen according to an embodiment. FIG. 10, a,shows an image 1001 recorded by an image capturing device e.g. an imagecapturing device of an endoscope. Blood vessels 1002 in the image 1001are not enhanced. The image 1001 may be processed to improve its overallquality e.g. to correct colors, set contrast, brightness etc. A part ofthe touch-screen is used to display a user interface configured to turnon enhancement of blood vessels and control the strength of theenhancement. The user interface may comprise a button 1003, configuredto allow a user to turn the enhancement of the blood vessels on/off. Theuser interface may comprise one or more enhancement level selectors,e.g. buttons 1004, 1005, configured to allow a user to control thestrength of the enhancement. The user interface may comprise anenhancement indicator 1006 for indicating the selected strength of theenhancement. The enhancement indicator 1006 may further function as anenhancement level selectors, e.g. a slider, whereby a user may slide theindicator 1006 to a desired position to select a particular strength ofthe enhancement. FIG. 10, a, shows an un-enhanced image, FIG. 10, b,shows an image enhanced with a medium strength, FIG. 10, c, shows animage enhanced with a high strength, and FIG. 10, d, shows an imageenhanced with a low strength. A visual identifier 1007 such, as a symbolor icon, may be inserted into the enhanced image to show to the userthat the image has been enhanced. The touch-screen may show live images,where the user interface is configured to turn on enhancement of bloodvessels and control the strength of the enhancement on the live images.The touch-screen may also show one or more recorded images, where theuser interface is configured to turn on/off enhancement of blood vesselsand control the strength of the enhancement on the one or more recordedimages.

FIG. 11 shows a flowchart of another embodiment of a method of enhancingthe visibility of blood vessels in a color image. The color image has aplurality of color channels and a plurality of pixels, wherein themethod comprises for at least some of the plurality of pixels the stepsof: 1101 processing data obtained from a first color channel togetherwith data obtained from a second color channel to determine a value of afirst parameter indicative of the intensity in the red spectrum relativeto the total intensity of the pixel; 1102 receiving user inputcomprising a first value of a user parameter; and 1103 using said valueof said first parameter and said first value of a user parameter toalter said pixel, the first value of the user parameter being based onthe user input, and wherein the strength of the alteration is dependenton both the value of said first parameter and the first value of saiduser parameter.

FIG. 12 shows a flowchart of a method of changing the enhancement of arecorded enhanced image according to an embodiment of the disclosure.The method comprises: 1201 storing a first enhanced image on the storageunit; 1202 storing on the storage unit an original un-enhanced image orimage data capable of re-creating the original un-enhanced image basedon the stored enhanced image; 1203 obtaining a second value of a userparameter based on user input; and 1204 creating a second enhanced imagebased on the original un-enhanced image and the second value of the userparameter, the second enhanced image being enhanced with a differentstrength than the first enhanced image.

The second enhanced image can also be created by saving intermediateimages obtained during the processing of the base image to obtain thefirst enhanced image. Using intermediate images saves processing stepsin that normalization and other processing does not have to beduplicated. The intermediate images are those that suffice to create anenhanced image prior to using the value of the user parameter. Theseinclude, for example, the first parameter image, the first intensitydifference image, the LP filtered color images, or the normalized colorimages. If the base color image is used, the additional processing couldsimply be to use the first parameter image with the user value to createthe second enhanced image. This reduces processing at the expense ofsaving an additional image. If the first enhanced image is saved,further processing includes undoing the first enhancement and thenapplying the second user value.

Additional/Alternative embodiments: Some of the embodiments above, theembodiments below, and some of the appended claims are described withreference to endoscopes or blood vessels. It should be understood,however, that the disclosed features are applicable to any videoscope todetect colored masses in images and that the reference to blood vesselsis to illustrate a particularly useful application of the invention,without limiting the invention to the enhancement of images includingvessels.

1. A method of enhancing the visibility of blood vessels in a colourimage captured by an image capturing device of a medical device, saidcolour image having a plurality of colour channels and having aplurality of pixels, wherein said method comprises for at least some ofsaid plurality of pixels the steps of:

(a) processing data obtained from a first colour channel together withdata obtained from a second colour channel to determine a value of afirst parameter indicative of the intensity in the first color channelrelative to the total intensity of said pixel;

(b) using said value of said first parameter to alter said pixel,

wherein said first parameter has at least three possible values, andwherein the strength of the alteration is dependent on the value of saidfirst parameter

2. A method according to embodiment 1, wherein step (a) comprises:processing data obtained from a first colour channel together with dataobtained from a second colour channel and data obtained from a thirdcolour channel to determine a value of said first parameter.

3. A method according to embodiment 2, wherein said data obtained fromthe first colour channel is processed together with said data obtainedfrom the second colour channel to create a value of a first subparameter, said data obtained from said first colour channel isprocessed together with said data obtained from said third colourchannel to create a value of a second sub parameter, and wherein saidvalue of said first sub parameter is processed together with said valueof said second sub parameter to create said value of said firstparameter.

4. A method according to embodiment 3, wherein both said value of saidfirst sub parameter and said value of said second sub parameter areindicative of the intensity in the first color channel relative to thetotal intensity of said pixel.

5. A method according to any one of embodiments 1 to 4, wherein step (a)comprises subtracting said data obtained from the second colour channelfrom said data obtained from the first colour channel.

6. A method according to any one of embodiments 1 to 5, wherein parts ofthe colour image having no blood vessels are substantially unaltered anddisplayed with normal colours.

7. A method according to any one of embodiments 1 to 6, wherein saidmethod further comprises: determining a value of a second parameterindicative of the intensity of said pixel and wherein said value of saidfirst parameter together with said value of said second parameter isused to alter said pixel.

8. A method according to any one of embodiments 1 to 7, wherein saidplurality of colour channels are normalized prior to being processedtogether.

9. A method according to embodiment 8, wherein a low pass filtered imageis created for each of said plurality of colour channels indicating alocal average for each pixel, and wherein each colour channel isnormalized using its low pass filtered image.

10. A method according to any one of embodiments 1 to 9, wherein a valueof a third parameter is created based on user input, and wherein thealteration is dependent on both said value of said first parameter andsaid value of said third parameter, whereby the user may control thestrength of the alteration.

11. A method according to any one of embodiments 1 to 10, wherein a highvalue of the first parameter indicates a high intensity in the firstcolor channel relative to the total intensity of said pixel and a lowvalue of the first parameter indicates a low intensity in the firstcolor channel relative to the total intensity of said pixel.

12. A method according to embodiment 11, wherein values of the firstparameter that are among the 50% highest of all possible values resultsin alterations that are more significant than the alterations thatresults from values of the first parameter that are among the 50% lowestof all possible values.

13. A method according to embodiments 11 or 12, wherein for at least 50%of the possible values of said first parameter an increase in the valueof the first parameter results in an increase in the strength of thealteration.

14. A method according to any one of embodiments 1 to 13. wherein thealteration of said pixel is independent of the intensity in the greenspectrum relative to the blue spectrum.

A method according to any one of embodiments 1 to 14, wherein the firstcolor channel corresponds to the red spectrum.

15. An image processing device for enhancing the visibility of bloodvessels in a colour image, said image processing device comprising aprocessing unit operationally connectable to an image capturing deviceof a medical device, wherein said processing unit is configured toreceive a colour image having a plurality of colour channels from saidimage capturing device, said colour image has a plurality of pixels andwherein said processing unit further is configured to for at least someof said plurality of pixels perform the steps of:

(a) process data obtained from a first colour channel together with dataobtained from a second colour channel to determine a value of a firstparameter indicative of the intensity in the first color channelrelative to the total intensity of said pixel;

(b) using said value of said first parameter to alter said pixel,

wherein said first parameter has at least three possible values, andwherein the strength of the alteration is dependent on the value of saidfirst parameter.

16. An image processing device according to embodiment 15, wherein step(a) comprises: processing data obtained from a first colour channeltogether with data obtained from a second colour channel and dataobtained from a third colour channel to determine a value of said firstparameter.

17. An image processing device according to embodiment 16, wherein saiddata obtained from the first colour channel is processed together withsaid data obtained from the second colour channel to create a value of afirst sub parameter, said data obtained from said first colour channelis processed together with said data obtained from said third colourchannel to create a value of a second sub parameter, and wherein saidvalue of said first sub parameter is processed together with said valueof said second sub parameter to create said value of said firstparameter.

18. An image processing device according to embodiment 17, wherein bothsaid value of said first sub parameter and said value of said second subparameter are indicative of the intensity in the first color channelrelative to the total intensity of said pixel.

19. An image processing device according to any one of embodiments 16 to18, wherein step (a) comprises subtracting said data obtained from thesecond colour channel from said data obtained from the first colourchannel.

20. An image processing device according to any one of embodiments 15 to19, wherein parts of the colour image having no blood vessels aresubstantially unaltered and displayed with normal colours.

21. An image processing device according to any one of embodiments 15 to20, wherein the processing unit is further configured to perform thestep of:

determining a value of a second parameter indicative of the intensity ofsaid pixel and wherein said value of said first parameter together withsaid value of said second parameter is used to alter said pixel.

22. An image processing device according to any one of embodiments 15 to21, wherein said plurality of colour channels are normalized prior tobeing processed together.

23. An image processing device according to embodiment 22, wherein a lowpass filtered image is created for each of said plurality of colourchannels indicating a local average for each pixel, and wherein eachcolour channel is normalized using its low pass filtered image.

24. An image processing device according to any one of embodiments 15 to23, wherein said image processing device is operationally connectable toan input unit for receiving user input and further configured to receivea user selected value of a third parameter from said input unit andwherein the alteration is dependent on both said value of said firstparameter and said value of said third parameter, whereby the user maycontrol the strength of the alteration.

25. An image processing device according to any one of embodiments 15 to24, wherein a high value of the first parameter indicates a highintensity in the first color channel relative to the total intensity ofsaid pixel and a low value of the first parameter indicates a lowintensity in the first color channel relative to the total intensity ofsaid pixel.

26. An image processing device according to embodiment 25, whereinvalues of the first parameter that are among the 50% highest of allpossible values results in alterations that are more significant thanthe alterations that results from values of the first parameter that areamong the 50% lowest of all possible values.

27. An image processing device according to embodiments 25 or 26,wherein for at least 50% of the possible values of said first parameteran increase in the value of the first parameter results in an increasein the strength of the alteration.

28. An image processing device according to any one of embodiments 15 to27, wherein the first color channel corresponds with the red spectrum,and wherein the alteration of said pixel is independent of the intensityin the green spectrum relative to the blue spectrum.

29. An image processing device for identifying potential pathologicalvascular structures, said image processing device comprising aprocessing unit operationally connectable to an image capturing deviceof a medical device, wherein said processing unit is configured toprocess an image adapted for computer image analysis using a machinelearning data architecture trained to identify potential pathologicalvascular structures in such images, wherein said image adapted forcomputer analysis is generated by processing a colour image having aplurality of colour channels recorded by said image capturing device,said colour image has a plurality of pixels wherein the processing ofsaid colour image comprises for at least some of said plurality ofpixels the steps of:

(a) process data obtained from a first colour channel together with dataobtained from a second colour channel to determine a value of a firstparameter indicative of the intensity in the first color channelrelative to the total intensity of said pixel;

(b) using said value of said first parameter to create a pixel value ofthe image adapted for computer image analysis.

30. An image processing device according to embodiment 29, wherein saidmachine learning data architecture is a supervised machine learningarchitecture provided with a training data set of images created bysteps a) and b), where a first subset of images of said training dataset show a pathological vascular structure and a second subset of imagesof said training data set show a healthy vascular structure.

31. An image processing device according to embodiment 30, wherein thetraining data set comprises a plurality of images showing vascularstructures of tumours.

32. An image processing device according to any one of embodiments 29 to31, wherein the pixel values of the image adapted for computer imageanalysis corresponds to the value of the first parameter optionallymultiplied with a weight value derived from said colour image; or thepixel values of the image adapted for computer image analysis is analtered pixel from said colour image altered using the value of saidfirst parameter and wherein the strength of the alteration is dependenton the value of said first parameter.

33. An image processing device according to any one of embodiments 29 to32, wherein the machine learning data architecture is an artificialneural network such as a deep structured learning architecture.

34. An image processing device according to any one of embodiments 29 to33, wherein the processing unit is directly operationally connectable tothe image capturing device and configured to receive the colour imageand perform steps a) and b) to create the image adapted for computerimage analysis.

35. An image processing device according to embodiment 34, wherein theprocessing unit is indirectly operationally connectable to the imagecapturing device via another image processing device, wherein said imageprocessing device is configured to receive said image adapted forcomputer image analysis from said another image processing device, saidanother image processing device being configured to receive the colourimage and perform steps a) and b) to create the image adapted forcomputer image analysis.

36. An image processing device according to embodiments 15 to 35,wherein the first color channel corresponds to the red spectrum.

37. A display unit for displaying images obtained by an image capturingdevice of a medical device, wherein said display unit comprises an imageprocessing device according to any one of embodiments 15 to 36.

38. An endoscope system comprising an endoscope and an image processingdevice according to any one of embodiments 15 to 36, wherein saidendoscope has an image capturing device and said processing unit of saidimage processing device is operationally connectable to said imagecapturing device of said endoscope.

39. An endoscope system according to embodiment 38, wherein theendoscope system further comprises a display unit according toembodiment 37, wherein said display unit is operationally connectable tosaid image capturing device of said endoscope and configured displaysaid captured images.

40. A computer program product comprising program code means adapted tocause a data processing system to perform the steps of the methodaccording to any one of embodiments 1 to 14, when said program codemeans are executed on the data processing system.

41. A computer product as in claim 40, wherein the first color channelcorresponds with the red spectrum.

42. A computer program product according to embodiments 40 or 41,wherein said computer program product comprises a non-transitorycomputer-readable medium having stored thereon the program code means.

Although some embodiments have been described and shown in detail, theinvention is not restricted to them, but may also be embodied in otherways within the scope of the subject matter defined in the followingclaims. In particular, it is to be understood that other embodiments maybe utilised and structural and functional modifications may be madewithout departing from the scope of the present invention.

In device claims enumerating several means, several of these means canbe embodied by one and the same item of hardware. The mere fact thatcertain measures are recited in mutually different dependent claims ordescribed in different embodiments does not indicate that a combinationof these measures cannot be used to advantage.

It should be emphasized that the term “comprises/comprising” when usedin this specification is taken to specify the presence of statedfeatures, integers, steps or components but does not preclude thepresence or addition of one or more other features, integers, steps,components or groups thereof.

References to “one embodiment,” “an embodiment,” “an exampleembodiment,” etc., indicate that the embodiment described may include aparticular feature, structure, or characteristic, but every embodimentmay not necessarily include the particular feature, structure, orcharacteristic. Moreover, such phrases are not necessarily referring tothe same embodiment.

The scope of the invention is to be limited by nothing other than theappended claims, in which reference to an element in the singular is notintended to mean “one and only one” unless explicitly so stated, butrather “one or more.” Moreover, where a phrase similar to “at least oneof A, B, or C” is used in the claims, it is intended that the phrase beinterpreted to mean that A alone may be present in an embodiment, Balone may be present in an embodiment, C alone may be present in anembodiment, or that any combination of the elements A, B or C may bepresent in a single embodiment; for example, A and B, A and C, B and C,or A and B and C.

We claim: 1-17. (canceled)
 48. A method of enhancing visibility of bloodvessels, the method comprising: processing pixel data from a red colorchannel of a color image together with pixel data from a green or a bluecolor channel of the color image to determine values of a firstparameter for pixels of the color image; receiving, from a userinterface actuated by a user, an enhancement level signal indicative ofa first value of a user parameter; and generating an enhanced image bychanging intensities of the pixels of the color image using the firstvalue of the user parameter and the values of the first parametercorresponding to the pixels.
 49. The method of claim 48, wherein thefirst parameter comprises a difference between intensities of a pixel inthe red channel and the green or the blue channel.
 50. The method ofclaim 49, wherein the processing includes obtaining a red-greenintensity difference as a difference between intensities of the pixel inthe red channel and the green channel, and obtaining a red-blueintensity difference as a difference between intensities of the pixel inthe red channel and the blue channel, and wherein the value of the firstparameter of the pixel is based on an average of the red-green intensitydifference and the red-blue intensity difference.
 51. The method ofclaim 50, further comprising, prior to obtaining the red-green intensitydifference and the red-blue intensity difference, normalizing theintensities of the pixels in the red channel, the green channel, and theblue channel.
 52. The method of claim 50, wherein using the first valueof the user parameter includes multiplying the value of the firstparameter by the first value of the user parameter before generating theenhanced image.
 53. The method of claim 48, wherein the processingincludes: low-pass (LP) filtering a red channel image of the color imageto create a LP red image; dividing the red channel image by the LP redimage to create a normalized red image; and creating a first intensitydifference image as a difference between the normalized red image and animage based on a green or blue channel image of the color image.
 54. Themethod of claim 53, wherein the first parameter image comprises thefirst intensity difference image, and wherein generating an enhancedimage includes subtracting the first parameter image from the redchannel image.
 55. The method of claim 54, wherein the first parameterimage comprises the first intensity difference image, and whereingenerating an enhanced image includes subtracting the first parameterimage from the color image.
 56. The method of claim 53, wherein theprocessing further includes: LP filtering a green or blue channel imageof the color image to create a LP green or blue image; dividing thegreen or blue channel image by the LP green or blue image to create anormalized green or blue image; and wherein the image based on a greenor blue channel image of the color image comprises the normalized greenor blue image.
 57. The method of claim 56, wherein the green or bluechannel image is the green channel image, and wherein the processingfurther includes: LP filtering a blue channel image of the color imageto obtain a LP blue image; dividing the blue channel image by the LPblue image to create a normalized blue image; obtaining a secondintensity difference image as a difference between the normalized redimage and the normalized blue image; and averaging the first intensitydifference image and the second intensity difference image to create thefirst parameter image.
 58. The method of claim 57, wherein generating anenhanced image includes subtracting the first parameter image from thered channel image, from the green channel image, and from the bluechannel image.
 59. The method of claim 57, wherein generating anenhanced image includes summing the red channel image with the greenchannel image and the blue channel image to create a second parameterimage, multiplying the first parameter image and the second parameterimage to create an alteration parameter image, and subtracting thealteration parameter image from the red channel image, the green channelimage, and the blue channel image, to generate the enhanced image. 60.The method of claim 59, wherein using the first value of the userparameter includes, before generating the enhanced image, multiplyingthe first parameter image or the second parameter image or thealteration parameter image by the first value of the user parameter. 61.The method of claim 48, further comprising: storing an image based onthe enhanced image or the color image; receiving a second enhancementlevel signal indicative of a second value of the user parameter, thesecond value being different than the first value; retrieving the storedimage; and creating a second enhanced image based on the stored imageand the second value of the user parameter.
 62. The method of claim 53,further comprising: storing an image based on the enhanced image or theoriginal image; storing the first parameter image or the first intensitydifference image; receiving a second enhancement level signal indicativeof a second value of the user parameter, the second value beingdifferent than the first value; retrieving the stored image and thefirst parameter image or the first intensity difference image; andcreating a second enhanced image based on the stored image, the secondvalue of the user parameter, and the first parameter image or the firstintensity difference image.
 63. The method of claim 48, furthercomprising processing the enhanced image with a machine learning dataarchiture trained with a library of health and pathological structuresto identify a pathological structure in the enhanced image.
 64. An imageprocessor for enhancing visibility of blood vessels, the image processorcomprising: a videoscope interface including a connection port adaptedto receive a connector of a videoscope having a camera operable togenerate color image data representative of a color image having a redcolor channel, a blue color channel, and a green color channel;graphical user interface (GUI) logic operable to present a GUI includingan enhancement level control to generate a first value of a userparameter; image processing logic structured to, when executed,implement a method to generate an enhanced image from the color imagedata, the method comprising: receiving the color image data generated bythe videoscope; processing pixel data from the red color channel withpixel data from the green or the blue color channel to determine valuesof a first parameter for pixels of the color image; and generating theenhanced image by changing intensities of the pixels of the color imageusing the first value of the user parameter and the values of the firstparameters corresponding to the pixel; and a housing at least partiallyenclosing the videoscope interface, the GUI logic, and the imageprocessing logic.
 65. The image processor of claim 64, furthercomprising a display module including a display screen, wherein the GUIlogic presents the enhanced image and the enhancement level control withthe display.
 66. The image processor of claim 64, wherein the processingincludes obtaining a red-green intensity difference as a differencebetween intensities of a pixel in the red channel and the green channel,and obtaining a red-blue intensity difference as a difference betweenintensities of the pixel in the red channel and the blue channel, andwherein the value of the first parameter of the pixel comprises anaverage of the red-green intensity difference and the red-blue intensitydifference.
 67. The image processor of claim 64, wherein the processing:low-pass (LP) filtering a red channel image of the color image to obtaina LP red image; LP filtering a green channel image of the color image toobtain a LP green image; LP filtering a blue channel image of the colorimage to obtain a LP blue image; dividing the red channel image by theLP red image to create a normalized red image; dividing the greenchannel image by the LP green image to create a normalized green image;dividing the blue channel image by the LP blue image to create anormalized blue image; obtaining a red-green intensity difference imageas a difference between the normalized red image and the normalizedgreen image; obtaining a red-blue intensity difference image as adifference between the normalized red image and the normalized blueimage; and averaging the red-blue intensity difference image and thered-green intensity difference image to create a first parameter image.68. An image processor for enhancing visibility of blood vessels, theimage processor comprising: a videoscope interface including aconnection port adapted to receive a connector of a videoscope having acamera operable to generate color image data representative of a colorimage having a red color channel, a blue color channel, and a greencolor channel; image processing logic structured to, when executed,implement a method to generate an enhanced image from the color imagedata, the method comprising: receiving the color image data generated bythe videoscope; processing pixel data from the red color channel withpixel data from the green or the blue color channel to determine valuesof a first parameter for pixels of the color image, wherein theprocessing includes obtaining a red-green intensity difference as adifference between intensities of a pixel in the red channel and thegreen channel and obtaining a red-blue intensity difference as adifference between intensities of the pixel in the red channel and theblue channel, wherein the value of the first parameter of the pixelcomprises an average of the red-green intensity difference and thered-blue intensity difference; and generating the enhanced image bychanging intensities of the pixels of the color image using the valuesof the first parameters corresponding to the pixel; and a housing atleast partially enclosing the videoscope interface and the imageprocessing logic.
 69. The image processor of claim 68, furthercomprising a display module including a display screen, wherein the GUIlogic presents the enhanced image with the display screen.
 70. The imageprocessor of claim 68, wherein the processing includes, before creatingthe red-green intensity difference and the red-blue intensitydifference, normalizing the pixel data from the red color channel, thegreen color channel, and the blue color channel.